Other sites

Superpixels in imager

Superpixels are used in image segmentation as a pre-processing step. Instead of segmenting pixels directly, we first group similar pixels into “super-pixels”, which can then be processed further (and more cheaply).

The current version of imager doesn’t implement them, but it turns out that SLIC superpixels are particularly easy to implement. SLIC is essentially k-means applied to pixels, with some bells and whistles.

We could use k-means to segment images based on colour alone. To get good results on colour segmentation the CIELAB colour space is appropriate, because it tries to be perceptually uniform.

We mostly manage to separate the petals from the rest, with a few errors here and there.
SLIC does pretty much the same thing, except we (a) use many more centers and (b) we add pixel coordinates as features in the clustering. The latter ensures that only adjacent pixels get grouped together.